Crystal Vis Final Report - Europa
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Crystal Vis Final Report Figure 1 The breadboard microscope with LED flash illumination. Figure 2 First tests in the breadboard microscope with the printed flow cell using Thiamine as the sample. Figure 3 An early 42 mm diameter sketch featuring a 10mm free flow-through sampling and a relay optic to extend the tube and get sensitive DIC optics out of the process.
Transcript of Crystal Vis Final Report - Europa
Crystal Vis Final Report
Figure 1 The breadboard microscope with LED flash illumination.
Figure 2 First tests in the breadboard microscope with the printed flow cell using Thiamine as the sample.
Figure 3 An early 42 mm diameter sketch featuring a 10mm free flow-through sampling and a relay optic to extend the tube and get sensitive DIC optics out of the process.
Figure 4 Free flow-through solution.
Figure 5 On the left a single-block aluminium parabolic dual mirror construction to connect the light from the LED to the fibre and on the right a similar structure to connect the light from the fibre to the condenser optics.
Figure 6 The Zeiss Axio microscope with LED transmission illumination (left) and one of the included Nomarski prisms (right).
Figure 7 Sketch of the (Plas)DIC accessory cubes.
Figure 8 Dual camera imaging optomechanics. The optical elements and rays have been displaced to the right for visibility.
Figure 9 Camera interface. Figure 10 Crystal detection program.
Figure 11: Examples of lysozyme crystals grown in our lab.
40 µm
Figure 12: Comparison of DIC objective (40X) with the normal objective using lysozyme crystals. Left: Normal image. Right: DIC image.
Figure 13: Example of image execution when opened with ImageJ/Fiji.
Figure 14: Application of enhanced local contrast. a: original image. b: treated image.
Figure 15: Example of the background noise removed using the background subtraction algorithm.
Figure 16: Applying the Gaussian blur and the smoothing filters. The images are shown for “before” (left) and “after” (right) the application of filters.
a b
Figure 17: Applying a general contrast function.
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Figure 18: Evaluation of the intensities and color channels using LUT functions. Left: Image before processing. Right: Image after processing using the algorithms “a” to “d”. 1: Images in the 32 bit greyscale mode. 2: Fire. 3: Spectrum. 4: Phase. 5: Thermal.
Figure 19: Applying the Brightness/Contrast parameters. The parameters should be adjusted until a good threshold is reached, while conserving the particle size and excess noise. Up: The original image before and after thresholding. Bottom: The processed image using the previous methods, before and after thresholding.
Figure 20: Thresholding methods for data segmentation.
Figure 21: Thresholding comparison of 8 bit and RGB images. Left: 8 bit image used for the start, with thresholding at 88 % signal saturation. Right: RGB image used for the start, with thresholding at 100 to 255 brightness intensity, 0 to 70 saturation intensity and full Hue levels.
Figure 22: Removing outliers from the binary image. Left: Original binary image. Right: Outliers removed, at 10 pixel settings
Figure 23: Fill holes function. Left: Original image. Right: Image after applying the function.
Figure 24: Watershed application. Left: Original image. Right: Image after applying the function. In this case an advanced plugin from BioVoxxel was used, to adjust the Erosion cycle number (set as 3).
Figure 25: Macro testing using different images.
Figure 26: Setting the scale bar and analyzing particles. The scale bar (left) allows the program to calculate parameters (right) based on a known distance and unit of measurement.
Figure 27: The result of a normal processing of a crystal image containing a lot of internal diffraction, image after standard processing, an orange heat filter showing the areas that are detected by standard algorithms and a Binary image of the result.
Figure 28: Canny edge detection before binary conversion. An 8 bit image was used. 1st Gaussian kernel radius: 5; Low threshold: 0.1; High threshold: 5. 2nd Gaussian kernel radius: 10; Low threshold: 0.1; High threshold: 5. The 3rd image was more useful and resulted in the identification of some crystals as shown below it.
Figure 29 a, b, c, d: Canny edge detection before binary conversion.
Figure 30: Image processing comparison of normal and DIC images.
Figure 31. Main elements and dimensions of the Crystalvis prototype. (1) external housing, (2) probe, (3) sampling gap, (4) prism position adjustment
Figure 31. Block diagram of the Crystalvis system.
Figure 32. Elements and principle of plasDIC technique.
Figure 34. Schematics of the Crystalvis optical system.
Figure 35. Light source specifications.
Figure 36. Parabolic reflectors design (TracePro)
Figure 37. Manufactured parts from the prototype. Parabolic reflector pairs used for coupling LED output to fibre input (left) and fibre output to condenser optics (right).
Figure 38. Specifications of the Crystalvis cameras.
Figure 39. Detailed illumination optics assembly.
Figure 40. Detailed microscope optics assembly.
Figure 41. Detailed plasDIC path assembly in outer housing.
Figure 42. Crystalvis system control board.
Figure 43. New sampling gap part.
Figure 44. Image quality improvement shown for in-situ air bubbles when raising bottom window by 2mm
Rounded edges
Gaskets
Gap
Figure 45. Standard (left) and adapted (right) cabinet
Figure 3. Electrical connections
Figure 47. Adjustment system for Nomarski prism position.
Camera 1 Camera 2 Power supply Configuration USB
Figure 48. Custom reaction vessel (front view).
FIGURE 50: CRYSTALVIS FOLDERS STRUCTURE
FIGURE 49: CRYSTALVIS DATABASE (DATALOG SCREEN)
FIGURE 55: MACRO TEMPLATE
FIGURE 51: EXPERIMENT FOLDER
FIGURE 53: EXPERIMENT/SOURCE FOLDER
FIGURE 54: EXPERIMENT/ANALYSIS FOLDER
FIGURE 52: ANALYSIS RESULTS
FIGURE 56: MAIN WINDOW
FIGURE 57: USER INTERFACE SECTIONS
FIGURE 60: ACQUISITION AND ANALYSIS PARAMETERS
FIGURE 59: CAPTURED IMAGE EXPLORE
FIGURE 58: CAPTURED IMAGE PREVIEW
FIGURE 61: HISTOGRAM AND TRENDLINE
FIGURE 63: CRYSTALVIS CONFIGURATION FILE
FIGURE 62 AUTOMATIC ACQUISITION MODE
FIGURE 65: IMAGEJ FOLDER
FIGURE 64: CAMERA SETTINGS
FIGURE 66: CAMERA SETTINGS
Table 1- number of units of the CRYSTAL-VIS technology sold 2017-2021
Table 2- Revenue generation potential and economic benefits for the supply SMEs
Table 3 - Potential economic benefits for the end-user SME and Other Participant
Number of units sold 2017 2018 2019 2020 2021 TotalEurope 10 20 40 80 160 310
Global 2 6 12 24 48 92
Total 12 26 52 104 208 402
2017 2018 2019 2020 2021 Total
INNOPHARMA Supply of the complete CRYSTAL-VIS unit 1,407,000.00 € 2,814,000.00 € 4,783,800.00 € 8,160,600.00 € 10,974,600.00 € 28,140,000.00 € 47
J&M ANALYTIC Supply of instrument components 603,000.00 € 1,206,000.00 € 2,050,200.00 € 3,497,400.00 € 4,703,400.00 € 12,060,000.00 € 202,010,000.00 € 4,020,000.00 € 6,834,000.00 € 11,658,000.00 € 15,678,000.00 € 40,200,000.00 € 67Totals
Short name Type of Exploitation
Estimated Economic Benefits
New Jobs
2017 2018 2019 2020 2021 Total
LABIANA Uptake of system in their API facilities 350.000,00 € 367.500,00 € 385.875,00 € 405.168,75 € 425.427,19 € 1.933.970,94 € 3,2
TOPCHEM Uptake of system in their API facilities 130.000,00 € 136.500,00 € 143.325,00 € 150.491,25 € 158.015,81 € 718.332,06 € 1,0
NUTRA Uptake of system in their APR R&D facilities 81.000,00 € 94.770,00 € 112.776,30 € 138.714,85 € 173.393,56 € 600.654,71 € 1,0
561.000,00 € 598.770,00 € 641.976,30 € 694.374,85 € 756.836,56 € 3.252.957,71 € 5,3
Short name Type of Exploitation
Estimated Economic Benefits New Jobs
Totals
Participating SME and OTHER End-users:
LABIANA, TOPCHEM, NUTRA
Protected RTD results (precompetitive)
Further dev. & demo work
Industrial CRYSTAL-VIS system
CRYS
TAL-
VIS
supp
ly &
val
ue
chai
n
Licensing Agreements with OEMs
Component, software and equipment suppliers:
INNOPHARMA, J&M ANALYTIK
Distribution Agreements
European & Global markets
CRYSTAL-VIS Business Plan &
Other Innovation Related Activities
Steps foreseen to ensure the SMEs can assimilate and exploit the RTD results
Envisaged Exploitation Routes
Table 4
Project Result Number Description
Type of Exploitation Remuneration
Type of Exploitation Remuneration
Type of Exploitation Remuneration
Type of Exploitation Remuneration
Type of Exploitation Remuneration
1
CRYSTAL-VIS procompetitive prototype unit available for further dissemination Ownership (40%) 119,167.50 €
Preferential Use 11,800.00 €
Ownership (20%) 41,950.00 €
Ownership (20%) 41,950.00 € Ownership (20%) 56,610.00 €
2
Statistical validation of the CRYSTAL-VIS system for characterising the physical properties of crystals Ownership (40%) 71,500.50 €
Preferential Use 11,800.00 €
Ownership (20%) 41,950.00 €
Ownership (20%) 41,950.00 € Ownership (20%) 56,610.00 €
3
Knowledge for the scale up of the hardware system and the chemometric models
Patent; Ownership 286,002.00 €
Preferential Use 11,800.00 € Preferential Use 41,950.00 €
Preferential Use 41,950.00 € 75,480.00 €
4
Knowledge for the optoelectronic and microelectronic modules of the system
Preferential Use 11,800.00 €
Preferential Use 41,950.00 €
Preferential Use 41,950.00 €
Patent; Ownership
INNOPHARMA 476,670.00 € LABIANA 47,200.00 € TOPCHEM 167,800.00 € NUTRA 167,800.00 € PR 188,700.00 €1,048,170.00 €Total Remuneration
NUTRA3 4 5
J&M ANALYTIC10
Subtotals
INNOPHARMA LABIANA TOPCHEMParticipant NameParticipant Number 1
